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About

I am a third-year PhD student in the Department of Applied Math and Statistics at Johns Hopkins, advised by Gregory Eyink. Previously, I obtained a B.S. in Applied Mathematics from Tufts University. At Tufts, I was advised by Bruce Boghosian and my senior thesis was advised by Abiy Tasissa.

Research

My research focuses on spontaneous stochasticity, which has emerged as a key concept for understanding turbulence and its statistical structure. A flow is said to exhibit spontaneous stochasticity if, in the infinite-Reynolds-number limit (Re \(\to \infty\)), the probability distribution over admissible weak solutions remains nontrivial and is universal—that is, it does not collapse to a single deterministic solution and is independent of the specific regularizations and perturbations. I am developing a numerical Renormalization Group scheme to study spontaneous stochasticity in the Kelvin-Helmholtz instability. In addition, I study a 1D model of spontaneous stochasticity using the Functional Renormalization Group with kernel approximation methods. I am also interested in studying vortex sheets in the statistical setting and extending existing mathematical results in this direction.

Contact

Email: mhudes1 {at} jh {dot} edu